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. Your competencies We thus imagine that you: have a strong background in digital signal processing and machine learning; have substantial experience with scientific computing in Python/C++/ROS; know
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Computer Science and Mathematics. A background in algorithm design and implementation combined with solid programming skills (e.g., Java, C, C++, Python), is highly valued. Candidates are expected to contribute
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Neural Networks Deep Learning and Uncertainty Quantification Python and ML frameworks (TensorFlow, PyTorch, JAX) Reproducible and open-science practices Experience with geospatial, environmental
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skills with the ability to connect theoretical modeling to practical, experimental data. experience with relevant computational tools (e.g., MATLAB, Python, or similar scientific programming environments
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programming skills in Python are essential, along with the ability to design experiments, analyze results, and interpret findings. Knowledge of optimization techniques, statistical modeling, and data management
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stronginterest and experience with GIS data and tools for urban mobility with someprogrammingskills of Python/R, JavaScript, database management environments, Geographical AI and machine learning workflows
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learn new advanced analysis techniques (e.g., in Matlab, R, or Python) if relevant for the task. Write up research results in the form of journal articles. Participate in and co-arrange national and